class_docstr: Regresses one or more floating point values given a single document.
  
  For a full list of configuration options, see `finetune.config`.
  
  :param config: A config object generated by `finetune.config.get_config` or None (for default config).
  :param \**kwargs: key-value pairs of config items to override.
class_docstr_tok: ["Regresses","one","or","more","floating","point","values","given","a","single","document",".","For","a","full","list","of","configuration","options",",","see","`","finetune.config","`",".",":","param","config",":","A","config","object","generated","by","`","finetune.config.get_config","`","or","None","(","for","default","config",")",".",":","param","\\","*","*","kwargs",":","key-value","pairs","of","config","items","to","override","."]
code: def _get_input_pipeline(self):
      return RegressionPipeline(self.config)
  
file_path: finetune/finetune/target_models/regressor.py
imports: import numpy
  from finetune.base import BaseModel
  from finetune.encoding.target_encoders import RegressionEncoder
  from finetune.nn.target_blocks import regressor
  from finetune.input_pipeline import BasePipeline
label_desc: Use image node_id 1 for calling the Regressor obj's underlying member method code with example usage: obj._get_input_pipeline() and returns: RegressionPipeline